Digitizing Intelligence to Optimize the Customer Experience

Digitizing Intelligence to Optimize the Customer Experience
Digitization implies continuous improvement.

To optimize the customer experience, modern digital enterprises need to provide alignment of the customer with the rest of the organizations – especially the departments, units, or teams that are involved in responding to the customer. Digitization implies continuous improvement. Thus the digital enterprise needs to also change its policies, approaches, and responsiveness to achieve improvements of customer experience measures.

This might involve analysis of customer transactions as well as the sentiment of the customer that is often expressed via social channels. Most importantly, digital transformation needs a digitization platform to achieve speed and a rhythm of change that adapts to increasingly demanding customer expectations as well as the volatility emanating from market disruptions. There are two main sources of “intelligence” that need to be leveraged in a digitally transformed enterprise: knowledge (policies, business rules) that is sourced from the head of experts, and knowledge that is mined and discovered from data (increasingly Big Data). Decisioning then can leverage both of these sources to transform the customer experience. This intelligence empowers the business to make changes and assist operations (customer service representatives) to quickly resolve customer issues. Through incorporating intelligent decisioning within CRM organizations can:

  • Seamlessly manage the multi-channel experience, where the customer can start an interaction in one channel, say a mobile device, and continue consistently through another channel, say the Web or when interacting with a customer service representative.

  • Act like one company to your customer: since dynamic case management can involve multiple sub-cases throughout the enterprise end to end, and cause the collaboration of tasks for customer objectives.

  • Personalize the Interactions: CRM should allow the different customers to be treated differently. For example, offering the most appropriate discount depending on the type of customer or product or location or service

  • Assist the Customer Service Representative: Intelligence in decisioning can help operations (e.g. CSRs) resolve customer requests or issues as quickly or efficiently as possible.

  • Empowering the Business: The knowledge of business strategies at a high level and business policies driving CRM often reside in the head of experts. These business-savvy knowledge workers need to be empowered to digitize their knowledge and make quickly changes to policies or procedures.

Mature digital enterprises have a healthy balance (even a “champion challenge”) between discovered knowledge (from data or information) and authored knowledge (from knowledge workers). More specifically, the sources of intelligence for decisioning emanate from:

  1. Business rules (as discussed in the previous section) that are authored by experts or knowledge workers;

  2. Demographic, census or other externally sourced data;

  3. Transactional data, from the enterprise information systems within the organization;

  4. Data warehouses and data marts that aggregate in multi-dimensional databases data from many sources;

  5. Data and information that is gathered from multiple social channels: Tweets, Facebook, Snapchat to name a few;

  6. Increasing, data gathered through the connected customer IoT devices – including wearables, connected vehicles, connected homes, connected appliances: to name a few.

In modern digitally transformed enterprises, the complete spectrum of intelligence for decisioning to optimize the customer experience is supported: pre-determined from heads of knowledge workers and experts; predictive models discovered from historic data; and decision strategies that learn and adapt to changes in customer behavior or market dynamics. Increasingly, the customer behavior is captured through the IoT devices that connect the customer to the service and product providers. Of course, most importantly this multi-dimensional intelligence needs to be operationalized and acted upon through digitized customer interactions as well as processes and dynamic cases that connect the customer to the digital enterprise.